TL;DR: The authors embed task instructions in a vector space with a language model, and train a sensorimotor-controlling model on top to perform tasks given the

TL;DR: The authors embed task instructions in a vector space with a language model, and train a sensorimotor-controlling model on top to perform tasks given the instruction embeddings. The authors find that the models generalize to previously unseen tasks, specified in natural language. Moreover, the authors show that the hidden states learn to represent task subcomponents, which helps explains why the model is able to generalize.